Modeling Development in Plant Sciences (Summer School): June 21-23, Muerren


Program Summer School 2012 June, 21-23, Muerren, CH 

Location: Hotel Regina 

Modeling Development in Plant Sciences 


Swiss Portal for Plant Science ( and 

Program Summer School 2012 June, 21-23, Muerren, CH 

Location: Hotel Regina 

Modeling Development in Plant Sciences MODELING DEVELOPMENT IN PLANT SCIENCES June, 21-23, 2012 2


• Christian Hardtke, Biophore Building, DBMV, University of Lausanne, Switzerland

• Christian Fankhauser, Genopode Building CIG, University of Lausanne, Switzerland


Invited Speakers: 

• Cris Kuhlemeier (UniBe, Switzerland)

• Stefan Kepinski (University of Leeds, UK)

• Richard Smith (UniBe, Switzerland)

• Jan Traas (ENS Lyon, France)

• Christian Fleck (University of Freiburg, Germany)

• Markus Owen (University of Nottingham, UK)


Thursday 21st June 

14:00-14:30 Welcome and registration

14:30-17:45 Exercises for the students with Pierre Barbier de Reuille (Uni Bern) and Micha Hersch (Uni Lausanne)

17:45-18:45 Apéro

18:45-20:00 Diner

20:00-21:00 Cris Kuhlemeier

System Biology of Phyllotaxis 

21:00- Free Time (socialisation, Bar open…)

Friday 22nd June 

7:30-8:30 Breakfast

08:30-10:00 Paper discussion 1*

10:00-10:30 Coffee break

10:30-12:00 Paper discussion 2* MODELING DEVELOPMENT IN PLANT SCIENCES June, 21-23, 2012 3

* the PIs will be asked to provide papers that will be discussed in small groups of students with one PIs. The precise format of this will be decided based on the number of attendees.

12:00-14:30 Extended lunch break

14:30-15:30 Christian Fleck

Increasing the understanding of phytochrome signaling through theory and experiment 

15:30-16:30 Jan Traas

From genes to shape: morphodynamics at the shoot apical meristem 

16:30-17:00 Coffee break

17:00-18:00 Markus Owen

Integrating plant gene regulatory networks with multi-scale tissue models 

18:00-18:45 Poster session

18:45-20:15 Diner

20:15-22:00 Poster session (continued) + drinks

Saturday 23rd June 

7:30-8:30 Breakfast

8:30-9:30 Stephan Kepinski

Context, specificity and self-organisation in auxin signalling 

9:30-10:00 Coffee break

10:00-11:00 Richard Smith

Plant patterning by auxin transport-feedback mechanisms 

11:00-12:00 Final discussion

12:00 Certificates and departure MODELING DEVELOPMENT IN PLANT SCIENCES June, 21-23, 2012 4


System Biology of Phyllotaxis 

Cris Kuhlemeier, University of Bern, Institute of Plant Sciences, Bern, Switzerland

Phyllotaxis, the regular arrangement of leaves or flowers around a plant stem, is an example of developmental pattern formation and organogenesis. Phyllotaxis is characterized by the divergence angles between the organs, the most common angle being 137°, the golden angle. This quantitative aspect makes phyllotaxis an unusual developmental problem. Models of phyllotaxis must explain its de novo establishment in the radially symmetric embryo, its stable maintenance and the transitions between patterns. I will describe the experiments that indicate that the central regulator of phyllotaxis consists of a positive feedback loop between auxin and its transporter, the PIN1 protein. Mathematical modeling shows that such a regulatory loop can generate regularly spaced auxin maxima within the shoot apical meristem, which cause differential gene expression, localized growth, and organ development. In our recent work we study how the environment interacts with this regulatory system and how downstream morphogenetic processes feedback on it.

Increasing the understanding of phytochrome signaling through theory and experiment 

Christian Fleck, University of Freiburg, Centre for Biological systems Analysis, Freiburg, Germany

Light is one of the most important abiotic environmental factors regulating plant growth and development throughout their entire life cycle. To monitor the spectral composition and intensity of the ambient light environment, plants have evolved multiple photoreceptors, including the five-membered phytochrome family. The light induced plant responses attributed to the phytochromes are manifold. Traditional biological approaches are very efficient on obtaining information on individual components of the light signaling system. However, they have limitations when it comes to the complex dynamic behavior that arises from the dynamic cycling between the active and inactive state of the phytochromes and from the interaction between different components within the light signaling pathway. Mathematical models help to integrate disparate molecular details and elucidate the underlying concept of an observed phenomenon. Such models provide a powerful tool for in silico testing of new hypotheses as well as discriminating among possible hypotheses. Models can guide the experimental efforts by leading the experiments towards issues that are important for validation and/or refinement of hypotheses. Such an iteration between experiments and modeling can be extremely productive in the analysis of complex systems. We discuss two recent examples for a fruitful joint theory-experiment approach from phytochrome A and phytochrome B signaling. MODELING DEVELOPMENT IN PLANT SCIENCES June, 21-23, 2012 5

Integrating plant gene regulatory networks with multi-scale tissue models 

Markus Owen, University of Nottingham, School of Mathematical Sciences, Nottingham, UK

In this lecture I will discuss the development of gene regulatory network models underlying plant hormone signalling, and how such models may be embedded in spatial models for tissue patterning and growth. I will show how a simple spatial model for Auxin signalling can be used to make novel predictions about root gravitropism, and how models can help to explain the importance of interacting feedback loops in Gibberellin signalling. Combining the Gibberellin signalling network with an empirical model for root growth shows that growth-induced gradients in hormones may determine the length of the root elongation zone. I will then discuss how to build multicellular models with realistic geometries, and multiscale models incorporating multiple hormones and crosstalk. To finish, important future directions will be highlighted, including how to model deforming and growing tissues.

Context, specificity and self-organisation in auxin signalling 

Stefan Kepinski, University of Leeds, Institute of Integrative and Comparative Biology, Leeds, UK

Auxin is a simple molecule with a remarkable ability to control plant growth, differentiation and morphogenesis. The mechanistic basis for this versatility appears to stem from the highly complex nature of the networks regulating auxin metabolism, transport and response. Using the root epidermis and the elongation of root hairs as a model, I will give an overview of the experimental and computational work my group is doing to understand how these heavily feed-back regulated and inter-dependent mechanisms can give rise to a system with self-organising properties capable of generating highly context-specific responses to auxin as a single, generic signal.

Plant patterning by auxin transport-feedback mechanisms 

Richard S. Smith – University of Bern, Switzerland.

Many patterning events in plants are regulated by the plant hormone auxin. There are so many things under the control of auxin that it is difficult to understand how a single hormone can do so much. Auxin is transported throughout the plant via a network of specialized membrane-bound import and export proteins, which are often differentially expressed and polarized depending on tissue types. In this presentation I will discuss models of plant patterning where auxin feeds back on its own transport, by controlling the action of its transporters. These models share many symmetry-breaking and patterning properties with reaction-diffusion systems. However, the diversity in patterning comes not from the addition of more morphogens, but rather by varying the mechanism that regulates the transporters. MODELING DEVELOPMENT IN PLANT SCIENCES June, 21-23, 2012 6 MODELING DEVELOPMENT IN PLANT SCIENCES June, 21-23, 2012 7

From genes to shape: morphodynamics at the shoot apical meristem 

Jan Traas1, Olivier Hamant1, Pradeep Das1, Vincent Mirabet1 , Arezki Boudoud1, Frédéric Boudon2 , Christophe Godi2

1 RDP, ENS-Lyon, 46 Allée d’Italie, 69364 Lyon cedex 07, France

2 UMR DAP (INRIA), Avenue Agropolis, 34398 Montpellier Cedex 5, France

During plant development the regulatory networks controlling growth and patterning must somehow interfere with physical processes to generate specific shapes. How this is achieved, i.e. how molecules assemble into complex systems with a particular form is not known in any organism. We are addressing this central issue in developmental biology using the shoot apical meristem of the higher plant Arabidopsis, which initiates all the aerial organs of the plant.

As a first step, we are currently trying to link the activity of regulatory genes to specific morphogenetic events. To this end, we have developed a computational pipeline, aimed at expressing gene function in terms of quantified, geometrical changes in tissue shape. Using this tool, we are monitoring anisotropy and growth rates in gene expression domains and in mutant backgrounds.

In parallel we have started to analyse the molecular basis of shape control. Using a combination of physical, mathematical and biological approaches we have provided evidence for a model where molecular networks would impact on two separable processes. First, we have identified a microtubule control of cell wall anisotropy, which feeds back on local stress and strain patterns. This process seems to define particular morphogenetic events and is coupled to the hormone-based control of overall growth patterns, associated with the rapid outgrowth of organs at particular locations.

Models in the form of virtual tissues are being developed to interpret the data and to propose precise hypotheses regarding gene function. These models, using finite element approaches, are able to express both mechanical and biochemical properties. Using 3D reconstructions of real floral meristems as a template we are currently trying to reproduce the growth patterns observed during flower development, taking into account the mechanistic insight we have obtained.